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f0d6538 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | import torch
def compare_tensors(
a: torch.Tensor,
b: torch.Tensor,
atol: float = 1e-5,
rtol: float = 1e-5,
) -> float:
"""
Compare two tensors and return the ratio of matching values.
Args:
a, b: Tensors to compare
atol, rtol: Absolute and relative tolerance thresholds
Returns:
ratio: Float between 0.0 and 1.0 indicating fraction of close values
"""
mask = torch.isclose(a, b, atol=atol, rtol=rtol)
matching = mask.sum().item()
total = mask.numel()
ratio = matching / total
# Log mismatches for debugging
if ratio < 1.0:
not_close_count = total - matching
pct_not_close = (not_close_count / total) * 100
print(f" {pct_not_close:.2f}% of values not close ({not_close_count}/{total})")
# Show details if small number of mismatches
if not_close_count <= 10:
mismatches = torch.where(torch.logical_not(mask))
print(f" Mismatch indices: {mismatches}")
print(f" Actual: {a[mismatches]}")
print(f" Expected: {b[mismatches]}")
return ratio
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